Triple
T10926364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osmosis Jones |
E258078
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Marc Hyman
Marc Hyman is an American screenwriter best known for co-writing the live-action/animated comedy film "Osmosis Jones."
|
E893532
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Marc Hyman | Statement: [Osmosis Jones, writer, Marc Hyman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marc Hyman Context triple: [Osmosis Jones, writer, Marc Hyman]
-
A.
Marc Rosen
Marc Rosen is an American businessman and talent agent best known as the younger husband of classic Hollywood actress Arlene Dahl.
-
B.
Mark Rosner
Mark Rosner is a screenwriter best known for co-writing the 1996 action film "The Rock."
-
C.
Mark Rosman
Mark Rosman is an American film and television director and screenwriter best known for his work on family and teen-oriented movies and series, including projects for Disney.
-
D.
Jay Landsman
Jay Landsman is a Baltimore police sergeant and homicide supervisor best known as a character in the television series "The Wire," inspired by and partly portrayed by the real-life Baltimore detective of the same name.
-
E.
Michael Haussman
Michael Haussman is an American director and filmmaker best known for his work on high-profile music videos and commercials.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Marc Hyman Triple: [Osmosis Jones, writer, Marc Hyman]
Generated description
Marc Hyman is an American screenwriter best known for co-writing the live-action/animated comedy film "Osmosis Jones."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marc Hyman Target entity description: Marc Hyman is an American screenwriter best known for co-writing the live-action/animated comedy film "Osmosis Jones."
-
A.
Marc Rosen
Marc Rosen is an American businessman and talent agent best known as the younger husband of classic Hollywood actress Arlene Dahl.
-
B.
Mark Rosner
Mark Rosner is a screenwriter best known for co-writing the 1996 action film "The Rock."
-
C.
Mark Rosman
Mark Rosman is an American film and television director and screenwriter best known for his work on family and teen-oriented movies and series, including projects for Disney.
-
D.
Jay Landsman
Jay Landsman is a Baltimore police sergeant and homicide supervisor best known as a character in the television series "The Wire," inspired by and partly portrayed by the real-life Baltimore detective of the same name.
-
E.
Michael Haussman
Michael Haussman is an American director and filmmaker best known for his work on high-profile music videos and commercials.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7709165188190aa30dd08deddade4 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e217369b648190914c58db6f6e0200 |
completed | April 17, 2026, 11:19 a.m. |
| NEDg | Description generation | batch_69e21d8aea2881908ac8f5225b8739c5 |
completed | April 17, 2026, 11:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e21eb18a1881908ded331db89063ed |
completed | April 17, 2026, 11:51 a.m. |
Created at: April 8, 2026, 9:22 p.m.